In vivo longitudinal monitoring of the inner retinal cellular morphology is of great importance in both clinical and experimental ophthalmology due to its importance in many blinding diseases, including glaucoma, the second leading cause of blindness in the adult population worldwide. At the cellular level, Ganglion Cells (GCs) damage and, ultimately, death often plays a central role in inner retinal disease progression. Recently, advances in OCT-based observation of highly translucent cell somas in the Ganglion Cell Layer (GCL) in both the living human and experimental animal eyes opened the door to noninvasive, label-free monitoring of RGC in vivo. However, a longitudinal validation of OCT's ability to follow individual RGC in experimental animals was still needed. To address this, we will report on our quantitative longitudinal studies in mice lines with fluorescently labeled ganglion cells. Here we used our custom-built mouse retinal Scanning Laser Ophthalmoscopy / Optical Coherence Tomography (SLO/OCT) system to acquire serial OCT volumes (with corresponding SLO intensity and fluorescence data) to provide input for Temporal Speckle Averaging (TSA) OCT volume processing method. To allow in vivo validation of TSA-OCT-based RGC quantification and monitoring, two mouse lines with fluorescently labeled RGC based on RGCs transcription factor (Brn3b-mCherry and Isl2-GFP) have been used and imaged simultaneously with fluorescence SLO (fSLO).
It has been recently demonstrated that structures corresponding to the cell bodies of highly transparent cells in the retinal ganglion cell layer could be visualized noninvasively both in the living human and mouse eyes by optical coherence tomography (OCT) via temporal averaging. Here, we further explored the application of volumetric temporal averaging in mice, with a focus on correlating the in vivo results with the ex vivo histology, on the same retinas, to verify the structures seen in the in vivo images, which will help to better understand the pathophysiology of these cells.
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